An Automated TW3-RUS Bone Age Assessment Method with Ordinal Regression-Based Determination of Skeletal Maturity.
The assessment of bone age is important for evaluating child development, optimizing the treatment for endocrine diseases, etc. And the well-known Tanner-Whitehouse (TW) clinical method improves the quantitative description of skeletal development based on setting up a series of distinguishable stag...
| Publicado en: | Journal of Digital Imaging Vol. 36; no. 3; pp. 1001 - 1016 |
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| Autores principales: | , , , , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=164473119&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 164473119 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2023 vid: 36 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 164473119 162029332 164473119 164473119 10.1007/s10278-023-00794-0 164473119 ppf: 1001 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An Automated TW3-RUS Bone Age Assessment Method with Ordinal Regression-Based Determination of Skeletal Maturity. aug: au: Zhang, Dongxu Liu, Bowen Huang, Yulin Yan, Yang Li, Shaowei He, Jinshui Zhang, Shuyun Zhang, Jun Xia, Ningshao affil: State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 361000, Xiamen, Fujian, China sug: subj: Age Determination by Skeleton Methods Diagnosis, Computer Assisted Bone Development In Infancy and Childhood Bone Development In Adolescence Funding Source Human Radius Radiography Ulna Radiography Fingers Radiography Metacarpal Bones Radiography Descriptive Statistics Male Female Deep Learning Neural Networks (Computer) Regression Algorithms Radiographic Image Enhancement Models, Statistical Logistic Regression China Child, Preschool Child Adolescence Child, Preschool: 2-5 years Child: 6-12 years Adolescent: 13-18 years Male Female ab: The assessment of bone age is important for evaluating child development, optimizing the treatment for endocrine diseases, etc. And the well-known Tanner-Whitehouse (TW) clinical method improves the quantitative description of skeletal development based on setting up a series of distinguishable stages for each bone individually. However, the assessment is affected by rater variability, which makes the assessment result not reliable enough in clinical practice. The main goal of this work is to achieve a reliable and accurate skeletal maturity determination by proposing an automated bone age assessment method called PEARLS, which is based on the TW3-RUS system (analysis of the radius, ulna, phalanges, and metacarpal bones). The proposed method comprises the point estimation of anchor (PEA) module for accurately localizing specific bones, the ranking learning (RL) module for producing a continuous stage representation of each bone by encoding the ordinal relationship between stage labels into the learning process, and the scoring (S) module for outputting the bone age directly based on two standard transform curves. The development of each module in PEARLS is based on different datasets. Finally, corresponding results are presented to evaluate the system performance in localizing specific bones, determining the skeletal maturity stage, and assessing the bone age. The mean average precision of point estimation is 86.29%, the average stage determination precision is 97.33% overall bones, and the average bone age assessment accuracy is 96.8% within 1 year for the female and male cohorts. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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